Will AI be able to write, compile, and unit test a single .c file to reproduce GPT-2 training from PyTorch code by 2026?
Will AI be able to write, compile, and unit test a single .c file to reproduce GPT-2 training from PyTorch code by 2026?
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Start date: April 9 , 2024
End date: April 9, 2026
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inspired from this tweet by Andrej Karpathy:
Btw writing the llm.c training code would imo be a very interesting, impressive, self-contained and very meta challenge for LLM agents.
The prompt is: Take the PyTorch code train_gpt2.py And write, compile and unit test a single .c file that reproduces the training: train_gpt2.c
The current models are not there, but we can check back in a year or two or so. If that worked...
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Wouldn't the training data now be 'contaminated' by Andrej's Github repo, making it impossible to judge this accurately?
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What is this?
What is Manifold?
Manifold is the world's largest social prediction market.
Get accurate real-time odds on politics, tech, sports, and more.
Or create your own play-money betting market on any question you care about.
Are our predictions accurate?
Yes! Manifold is very well calibrated, with forecasts on average within 4 percentage points of the true probability. Our probabilities are created by users buying and selling shares of a market.
In the 2022 US midterm elections, we outperformed all other prediction market platforms and were in line with FiveThirtyEight’s performance. Many people who don't like betting still use Manifold to get reliable news.
Why use play money?
Why use play money?Mana (Ṁ) is the play-money currency used to bet on Manifold. It cannot be converted to cash. All users start with Ṁ1,000 for free.
Play money means it's much easier for anyone anywhere in the world to get started and try out forecasting without any risk. It also means there's more freedom to create and bet on any type of question.
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